{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "79bc1341-0357-bd3b-f0fd-923783e8cb2f"
   },
   "source": [
    "Let us do some univariate analysis in this notebook and build simple regression models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "970e3273-0596-1ae2-f41b-8bd4f383e11f"
   },
   "outputs": [],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load in \n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn import linear_model as lm\n",
    "import kagglegym\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "8ab0f76f-6e12-71b6-64d2-f42ec4d88afa"
   },
   "source": [
    "Read the train file from Kaggle gym."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "f2400f0b-6036-8bcc-8b40-d5b121dc9e67"
   },
   "outputs": [],
   "source": [
    "# Create environment\n",
    "env = kagglegym.make()\n",
    "\n",
    "# Get first observation\n",
    "observation = env.reset()\n",
    "\n",
    "# Get the train dataframe\n",
    "train = observation.train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_cell_guid": "ac653533-ef0e-ff32-141e-d29fad827240"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(806298, 111)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "_cell_guid": "e5f46aaa-dc6b-b166-5ea5-af9f49566724"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>derived_0</th>\n",
       "      <th>derived_1</th>\n",
       "      <th>derived_2</th>\n",
       "      <th>derived_3</th>\n",
       "      <th>derived_4</th>\n",
       "      <th>fundamental_0</th>\n",
       "      <th>fundamental_1</th>\n",
       "      <th>fundamental_2</th>\n",
       "      <th>...</th>\n",
       "      <th>technical_36</th>\n",
       "      <th>technical_37</th>\n",
       "      <th>technical_38</th>\n",
       "      <th>technical_39</th>\n",
       "      <th>technical_40</th>\n",
       "      <th>technical_41</th>\n",
       "      <th>technical_42</th>\n",
       "      <th>technical_43</th>\n",
       "      <th>technical_44</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.370326</td>\n",
       "      <td>-6.316399e-03</td>\n",
       "      <td>0.222831</td>\n",
       "      <td>-0.213030</td>\n",
       "      <td>0.729277</td>\n",
       "      <td>-0.335633</td>\n",
       "      <td>1.132921e-01</td>\n",
       "      <td>1.621238</td>\n",
       "      <td>...</td>\n",
       "      <td>0.775208</td>\n",
       "      <td>-0.098557</td>\n",
       "      <td>-0.090948</td>\n",
       "      <td>-0.080027</td>\n",
       "      <td>-0.414776</td>\n",
       "      <td>0.00601</td>\n",
       "      <td>-0.028033</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.000783</td>\n",
       "      <td>-0.011753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0.014765</td>\n",
       "      <td>-3.806422e-02</td>\n",
       "      <td>-0.017425</td>\n",
       "      <td>0.320652</td>\n",
       "      <td>-0.034134</td>\n",
       "      <td>0.004413</td>\n",
       "      <td>1.142851e-01</td>\n",
       "      <td>-0.210185</td>\n",
       "      <td>...</td>\n",
       "      <td>0.025590</td>\n",
       "      <td>-0.098557</td>\n",
       "      <td>-0.090948</td>\n",
       "      <td>-0.080027</td>\n",
       "      <td>-0.273607</td>\n",
       "      <td>0.00601</td>\n",
       "      <td>-0.028033</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.000783</td>\n",
       "      <td>-0.001240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.010622</td>\n",
       "      <td>-5.057707e-02</td>\n",
       "      <td>3.379575</td>\n",
       "      <td>-0.157525</td>\n",
       "      <td>-0.068550</td>\n",
       "      <td>-0.155937</td>\n",
       "      <td>1.219439e+00</td>\n",
       "      <td>-0.764516</td>\n",
       "      <td>...</td>\n",
       "      <td>0.151881</td>\n",
       "      <td>-0.098557</td>\n",
       "      <td>-0.090948</td>\n",
       "      <td>-0.080027</td>\n",
       "      <td>-0.175710</td>\n",
       "      <td>0.00601</td>\n",
       "      <td>-0.028033</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.000783</td>\n",
       "      <td>-0.020940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>-9.463644</td>\n",
       "      <td>3.195843e+11</td>\n",
       "      <td>-0.835275</td>\n",
       "      <td>-0.856674</td>\n",
       "      <td>37.132420</td>\n",
       "      <td>0.178495</td>\n",
       "      <td>-1.254203e+09</td>\n",
       "      <td>-0.007262</td>\n",
       "      <td>...</td>\n",
       "      <td>1.035936</td>\n",
       "      <td>-0.098557</td>\n",
       "      <td>-0.090948</td>\n",
       "      <td>-0.080027</td>\n",
       "      <td>-0.211506</td>\n",
       "      <td>0.00601</td>\n",
       "      <td>-0.028033</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.000783</td>\n",
       "      <td>-0.015959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0.176693</td>\n",
       "      <td>-2.528418e-02</td>\n",
       "      <td>-0.057680</td>\n",
       "      <td>0.015100</td>\n",
       "      <td>0.180894</td>\n",
       "      <td>0.139445</td>\n",
       "      <td>-1.256869e-01</td>\n",
       "      <td>-0.018707</td>\n",
       "      <td>...</td>\n",
       "      <td>0.630232</td>\n",
       "      <td>-0.098557</td>\n",
       "      <td>-0.090948</td>\n",
       "      <td>-0.080027</td>\n",
       "      <td>-0.001957</td>\n",
       "      <td>0.00601</td>\n",
       "      <td>-0.028033</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000783</td>\n",
       "      <td>-0.007338</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  timestamp  derived_0     derived_1  derived_2  derived_3  derived_4  \\\n",
       "0  10          0   0.370326 -6.316399e-03   0.222831  -0.213030   0.729277   \n",
       "1  11          0   0.014765 -3.806422e-02  -0.017425   0.320652  -0.034134   \n",
       "2  12          0  -0.010622 -5.057707e-02   3.379575  -0.157525  -0.068550   \n",
       "3  25          0  -9.463644  3.195843e+11  -0.835275  -0.856674  37.132420   \n",
       "4  26          0   0.176693 -2.528418e-02  -0.057680   0.015100   0.180894   \n",
       "\n",
       "   fundamental_0  fundamental_1  fundamental_2    ...     technical_36  \\\n",
       "0      -0.335633   1.132921e-01       1.621238    ...         0.775208   \n",
       "1       0.004413   1.142851e-01      -0.210185    ...         0.025590   \n",
       "2      -0.155937   1.219439e+00      -0.764516    ...         0.151881   \n",
       "3       0.178495  -1.254203e+09      -0.007262    ...         1.035936   \n",
       "4       0.139445  -1.256869e-01      -0.018707    ...         0.630232   \n",
       "\n",
       "   technical_37  technical_38  technical_39  technical_40  technical_41  \\\n",
       "0     -0.098557     -0.090948     -0.080027     -0.414776       0.00601   \n",
       "1     -0.098557     -0.090948     -0.080027     -0.273607       0.00601   \n",
       "2     -0.098557     -0.090948     -0.080027     -0.175710       0.00601   \n",
       "3     -0.098557     -0.090948     -0.080027     -0.211506       0.00601   \n",
       "4     -0.098557     -0.090948     -0.080027     -0.001957       0.00601   \n",
       "\n",
       "   technical_42  technical_43  technical_44         y  \n",
       "0     -0.028033          -2.0      0.000783 -0.011753  \n",
       "1     -0.028033          -2.0      0.000783 -0.001240  \n",
       "2     -0.028033          -2.0      0.000783 -0.020940  \n",
       "3     -0.028033          -2.0      0.000783 -0.015959  \n",
       "4     -0.028033           0.0      0.000783 -0.007338  \n",
       "\n",
       "[5 rows x 111 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_values = train.mean(axis=0)\n",
    "train.fillna(mean_values, inplace=True)\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "815e3a2e-d838-9248-14f7-bbdd17b66595"
   },
   "source": [
    "**Correlation coefficient plot:**\n",
    "\n",
    "Let us look at the correlation of each of the variables with the target variables to get some important variables to be used for our next steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "_cell_guid": "3746958b-a312-87f6-9658-b1dbf3e83f36"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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11l0L7H5Luut1RJJfS3J5KeVJSw1GJiYOW2qZjDD97B897Zel9lP/R5v+9It+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g9YERF3An/OzOeqMZ9YvRuA89m1GqUlEXFQNaafUxJRBwJ/B7xEWbi28d4VlOTL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\nQsazfoxpvRjPepg584gxt9HbeySzZ88Yh9FovPj5rB9jWi/GU2M11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fAMsDQzBw9wy32U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Y8AIykMeqURQ00QDCZ8OljZcMBmhoiIGQ7t4/vr8TDyedpE/O6Zzk1+9X1Sn6/C7f76d/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\nSW3p/wPvJj+2bAb24wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7277c589b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now let us look at the correlation coefficient of each of these variables #\n",
    "x_cols = [col for col in train.columns if col not in ['id','timestamp','y']]\n",
    "\n",
    "labels = []\n",
    "values = []\n",
    "for col in x_cols:\n",
    "    labels.append(col)\n",
    "    values.append(np.corrcoef(train[col].values, train.y.values)[0,1])\n",
    "    \n",
    "ind = np.arange(len(labels))\n",
    "width = 0.9\n",
    "fig, ax = plt.subplots(figsize=(12,40))\n",
    "rects = ax.barh(ind, np.array(values), color='y')\n",
    "ax.set_yticks(ind+((width)/2.))\n",
    "ax.set_yticklabels(labels, rotation='horizontal')\n",
    "ax.set_xlabel(\"Correlation coefficient\")\n",
    "ax.set_title(\"Correlation coefficient\")\n",
    "#autolabel(rects)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "d890c2d3-62d9-0d65-d17c-d701b4d46ef4"
   },
   "source": [
    "As expected, the correlation coefficient values are very low and the maximum value is around 0.016 (in both positive and negative) as seen from the plot above.\n",
    "\n",
    "Let us take the top 4 variables from the plot above and do some more analysis on them alone.\n",
    "\n",
    " - technical_30\n",
    " - technical_20\n",
    " - fundamental_11\n",
    " - technical_19\n",
    "\n",
    "As a first step, let us get the correlation coefficient in between these variables. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "_cell_guid": "fe0d9c9c-ffc2-96e7-00ce-00575dfd36fb"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pfE3pQCRJkjQ4jecpBIiI5wDPBk7PzHsjYiwzrRRKkqSec0WTshoNNImIdSLi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\nfclXlAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f72763ff9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols_to_use = ['technical_30', 'technical_20', 'fundamental_11', 'technical_19']\n",
    "\n",
    "temp_df = train[cols_to_use]\n",
    "corrmat = temp_df.corr(method='spearman')\n",
    "f, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "# Draw the heatmap using seaborn\n",
    "sns.heatmap(corrmat, vmax=.8, square=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "43f48b6b-3e5b-68ee-153b-4f8e52d220c3"
   },
   "source": [
    "There is some negative correlation between 'technical_30' and 'technical_20'. \n",
    "\n",
    "As the next step, let us build simple linear regression models using these variables alone and see how they perform.\n",
    "\n",
    "Let us first build our models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "_cell_guid": "462135e2-fe24-ac8d-4461-b064cbce4ad3"
   },
   "outputs": [],
   "source": [
    "models_dict = {}\n",
    "for col in cols_to_use:\n",
    "    model = lm.LinearRegression()\n",
    "    model.fit(np.array(train[col].values).reshape(-1,1), train.y.values)\n",
    "    models_dict[col] = model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "f47f3427-d931-1fce-4f30-f10885d7e297"
   },
   "source": [
    "So we have built 4 univariate models using the train data.\n",
    "\n",
    "**Technical_30:**\n",
    "\n",
    "So we will start predicting with the model using 'technical_30' variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "_cell_guid": "175e00f9-b912-a0ca-9ef4-e1938432fc41"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Timestamp #1000\n",
      "Timestamp #1100\n",
      "Timestamp #1200\n",
      "Timestamp #1300\n",
      "Timestamp #1400\n",
      "Timestamp #1500\n",
      "Timestamp #1600\n",
      "Timestamp #1700\n",
      "Timestamp #1800\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'public_score': 0.01184566695251266}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col = 'technical_30'\n",
    "model = models_dict[col]\n",
    "while True:\n",
    "    observation.features.fillna(mean_values, inplace=True)\n",
    "    test_x = np.array(observation.features[col].values).reshape(-1,1)\n",
    "    observation.target.y = model.predict(test_x)\n",
    "    #observation.target.fillna(0, inplace=True)\n",
    "    target = observation.target\n",
    "    timestamp = observation.features[\"timestamp\"][0]\n",
    "    if timestamp % 100 == 0:\n",
    "        print(\"Timestamp #{}\".format(timestamp))\n",
    "        \n",
    "    observation, reward, done, info = env.step(target)\n",
    "    if done:\n",
    "        break\n",
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "a580bb5f-6c54-0845-ef0d-6133eaef7b7a"
   },
   "source": [
    "We are getting a public score of 0.011 using this variable.\n",
    "\n",
    "**Technical_20:**\n",
    "\n",
    "Now let us predict the test using our second univariate model which we have built."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "_cell_guid": "8398a98e-e624-24ba-21b6-4408eaab4757"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Timestamp #1000\n",
      "Timestamp #1100\n",
      "Timestamp #1200\n",
      "Timestamp #1300\n",
      "Timestamp #1400\n",
      "Timestamp #1500\n",
      "Timestamp #1600\n",
      "Timestamp #1700\n",
      "Timestamp #1800\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'public_score': 0.016952886918904748}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get first observation\n",
    "env = kagglegym.make()\n",
    "observation = env.reset()\n",
    "\n",
    "col = 'technical_20'\n",
    "model = models_dict[col]\n",
    "while True:\n",
    "    observation.features.fillna(mean_values, inplace=True)\n",
    "    test_x = np.array(observation.features[col].values).reshape(-1,1)\n",
    "    observation.target.y = model.predict(test_x)\n",
    "    #observation.target.fillna(0, inplace=True)\n",
    "    target = observation.target\n",
    "    timestamp = observation.features[\"timestamp\"][0]\n",
    "    if timestamp % 100 == 0:\n",
    "        print(\"Timestamp #{}\".format(timestamp))\n",
    "        \n",
    "    observation, reward, done, info = env.step(target)\n",
    "    if done:\n",
    "        break\n",
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "55d95eff-4ab2-a119-2117-9e08a6777d35"
   },
   "source": [
    "Using 'technical_20' as input variable, we are getting a public score of 0.0169 which is slightly better than the previous one.\n",
    "\n",
    "Submitting this model to the LB gave me a score of 0.006. I have exported the above script into a kernel and it can be accessed [here][1].  \n",
    "\n",
    "Let us do the same for our last two variables as well.\n",
    "\n",
    "**Fundamental_11:**\n",
    "\n",
    "\n",
    "  [1]: https://www.kaggle.com/sudalairajkumar/two-sigma-financial-modeling/univariate-model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "_cell_guid": "d6f91212-8fe3-762c-d4ab-8c648e24dbfa"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Timestamp #1000\n",
      "Timestamp #1100\n",
      "Timestamp #1200\n",
      "Timestamp #1300\n",
      "Timestamp #1400\n",
      "Timestamp #1500\n",
      "Timestamp #1600\n",
      "Timestamp #1700\n",
      "Timestamp #1800\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'public_score': -0.0018695971548146769}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get first observation\n",
    "env = kagglegym.make()\n",
    "observation = env.reset()\n",
    "\n",
    "col = 'fundamental_11'\n",
    "model = models_dict[col]\n",
    "while True:\n",
    "    observation.features.fillna(mean_values, inplace=True)\n",
    "    test_x = np.array(observation.features[col].values).reshape(-1,1)\n",
    "    observation.target.y = model.predict(test_x)\n",
    "    #observation.target.fillna(0, inplace=True)\n",
    "    target = observation.target\n",
    "    timestamp = observation.features[\"timestamp\"][0]\n",
    "    if timestamp % 100 == 0:\n",
    "        print(\"Timestamp #{}\".format(timestamp))\n",
    "        \n",
    "    observation, reward, done, info = env.step(target)\n",
    "    if done:\n",
    "        break\n",
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "dae84c5d-3e9c-899f-ca37-4fdb373b74be"
   },
   "source": [
    "**Technical_19:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "_cell_guid": "e6531aaf-dadf-77dd-c4f4-bec0e1eef347"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Timestamp #1000\n",
      "Timestamp #1100\n",
      "Timestamp #1200\n",
      "Timestamp #1300\n",
      "Timestamp #1400\n",
      "Timestamp #1500\n",
      "Timestamp #1600\n",
      "Timestamp #1700\n",
      "Timestamp #1800\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'public_score': 0.0066252988079944057}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get first observation\n",
    "env = kagglegym.make()\n",
    "observation = env.reset()\n",
    "\n",
    "col = 'technical_19'\n",
    "model = models_dict[col]\n",
    "while True:\n",
    "    observation.features.fillna(mean_values, inplace=True)\n",
    "    test_x = np.array(observation.features[col].values).reshape(-1,1)\n",
    "    observation.target.y = model.predict(test_x)\n",
    "    #observation.target.fillna(0, inplace=True)\n",
    "    target = observation.target\n",
    "    timestamp = observation.features[\"timestamp\"][0]\n",
    "    if timestamp % 100 == 0:\n",
    "        print(\"Timestamp #{}\".format(timestamp))\n",
    "        \n",
    "    observation, reward, done, info = env.step(target)\n",
    "    if done:\n",
    "        break\n",
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "c93b7f0a-20b1-9c0a-5ea2-2299eed59bd6"
   },
   "source": [
    "**Regression using all 4 variables:**\n",
    "\n",
    "Now let us build multiple regression model using all these 4 variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "_cell_guid": "c5d587be-c27d-4ad8-7c14-274aa89c86db"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Timestamp #1000\n",
      "Timestamp #1100\n",
      "Timestamp #1200\n",
      "Timestamp #1300\n",
      "Timestamp #1400\n",
      "Timestamp #1500\n",
      "Timestamp #1600\n",
      "Timestamp #1700\n",
      "Timestamp #1800\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'public_score': 0.019545566459911509}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols_to_use = ['technical_30', 'technical_20', 'fundamental_11', 'technical_19']\n",
    "\n",
    "# Get first observation\n",
    "env = kagglegym.make()\n",
    "observation = env.reset()\n",
    "train = observation.train\n",
    "train.fillna(mean_values, inplace=True)\n",
    "\n",
    "model = lm.LinearRegression()\n",
    "model.fit(np.array(train[cols_to_use]), train.y.values)\n",
    "\n",
    "while True:\n",
    "    observation.features.fillna(mean_values, inplace=True)\n",
    "    test_x = np.array(observation.features[cols_to_use])\n",
    "    observation.target.y = model.predict(test_x)\n",
    "    target = observation.target\n",
    "    timestamp = observation.features[\"timestamp\"][0]\n",
    "    if timestamp % 100 == 0:\n",
    "        print(\"Timestamp #{}\".format(timestamp))\n",
    "        \n",
    "    observation, reward, done, info = env.step(target)\n",
    "    if done:\n",
    "        break\n",
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "21dffde0-614b-65da-255d-595786961ec0"
   },
   "source": [
    "This multiple regression gave a score of 0.019 which is better than all univariate models. So probably submitting this model might give a better LB score.\n",
    "\n",
    "**Model with Clipping:**\n",
    "\n",
    "As we can see from this [script][1] which gives the best public LB score of 0.00911, clipping the 'y' values help. \n",
    "\n",
    "So let us dig a little deeper to see why the public LB score increased from 0.006 to 0.009 when we clip the 'y' values.\n",
    "\n",
    "  [1]: https://www.kaggle.com/bguberfain/two-sigma-financial-modeling/univariate-model-with-clip/run/482189/code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "_cell_guid": "0461ba59-efd2-f31c-3f2a-02ff17dc5433"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max y value in train :  0.0934978\n",
      "Min y value in train :  -0.0860941\n"
     ]
    }
   ],
   "source": [
    "print(\"Max y value in train : \",train.y.max())\n",
    "print(\"Min y value in train : \",train.y.min())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "d0d7c4ec-31ac-fe95-0f29-6ec4b626c32d"
   },
   "source": [
    "Let us now do the clipping and see the number of rows that will be discarded from the training. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "_cell_guid": "213232bf-3053-56f5-d424-e113ff2a5ee4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     796880\n",
       "False      9418\n",
       "Name: y, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "low_y_cut = -0.086093\n",
    "high_y_cut = 0.093497\n",
    "\n",
    "y_is_above_cut = (train.y > high_y_cut)\n",
    "y_is_below_cut = (train.y < low_y_cut)\n",
    "y_is_within_cut = (~y_is_above_cut & ~y_is_below_cut)\n",
    "y_is_within_cut.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "214c5a7d-b94b-dc62-f7b1-7e81fe4b1599"
   },
   "source": [
    "So there are 9418 rows in the training set that lie between (-0.086093 and -0.0860941) and (0.093497 and 0.0934978) in the training set. So many values in such a small range.\n",
    "\n",
    "As we can see from [anokas script][1], the distribution of 'y' values have two small spikes at both the ends. Probably values which are higher than these values are clipped in the training data and so not using these rows in our model building might be a good idea.\n",
    "\n",
    "\n",
    "\n",
    "Now let us re-train our model (using technical_20) by excluding these rows from the training.\n",
    "\n",
    "\n",
    "  [1]: https://www.kaggle.com/anokas/two-sigma-financial-modeling/two-sigma-time-travel-eda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "_cell_guid": "cc707a6b-c33e-da83-e631-2861b3659eec"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Timestamp #1000\n",
      "Timestamp #1100\n",
      "Timestamp #1200\n",
      "Timestamp #1300\n",
      "Timestamp #1400\n",
      "Timestamp #1500\n",
      "Timestamp #1600\n",
      "Timestamp #1700\n",
      "Timestamp #1800\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'public_score': 0.016922777420276997}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get first observation\n",
    "env = kagglegym.make()\n",
    "observation = env.reset()\n",
    "\n",
    "col = 'technical_20'\n",
    "model = lm.LinearRegression()\n",
    "model.fit(np.array(train.loc[y_is_within_cut, col].values).reshape(-1,1), train.loc[y_is_within_cut, 'y'])\n",
    "\n",
    "while True:\n",
    "    observation.features.fillna(mean_values, inplace=True)\n",
    "    test_x = np.array(observation.features[col].values).reshape(-1,1)\n",
    "    observation.target.y = model.predict(test_x).clip(low_y_cut, high_y_cut)\n",
    "    #observation.target.fillna(0, inplace=True)\n",
    "    target = observation.target\n",
    "    timestamp = observation.features[\"timestamp\"][0]\n",
    "    if timestamp % 100 == 0:\n",
    "        print(\"Timestamp #{}\".format(timestamp))\n",
    "        \n",
    "    observation, reward, done, info = env.step(target)\n",
    "    if done:\n",
    "        break\n",
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "ef4c89b0-66d5-3fd4-3760-2dcf2995ca9b"
   },
   "source": [
    "So we got almost same public score of 0.0169 with clip.\n",
    "\n",
    "But on the leaderboard, we are getting some improvement in the score from 0.006 to 0.009. \n",
    "\n",
    "Hope this gives a good starting point for building models. Happy Kaggling under new environment.!"
   ]
  }
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